SDM report
1 Dataset
The models are based on trawling data on the west coast
There are three data sources; IBTS, BITS and NATS
2 Trawl surveys
Information about the trawl surveys…
3 Catches
4 Predictors
Variables VIF
1 bTemp 4.043284
2 bSal 2.161882
3 Depth 3.196960
4 botCur 1.307152
5 slope 1.190949
6 fishInt 1.382509
7 maxT 3.904484
5 Presence / Absence models (Biomod2)
-=-=-=-=-=-=-=-=-=-=-=-=-=-=-= BIOMOD.models.out -=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
Modeling folder : C:/Github_projects/SDM_Claire/model output/20240917/PA
Species modeled : Plaice
Modeling id : Plaice_2005_2022_AllYear
Considered variables : bTemp bSal Depth botCur slope fishInt maxT
Computed Models : Plaice_allData_RUN1_GLM Plaice_allData_RUN1_GBM
Plaice_allData_RUN1_RF Plaice_allData_RUN1_XGBOOST Plaice_allData_RUN2_GLM
Plaice_allData_RUN2_GBM Plaice_allData_RUN2_RF Plaice_allData_RUN2_XGBOOST
Plaice_allData_allRun_GLM Plaice_allData_allRun_GBM Plaice_allData_allRun_RF
Plaice_allData_allRun_XGBOOST
Failed Models : Plaice_allData_RUN1_GAM Plaice_allData_RUN2_GAM
Plaice_allData_allRun_GAM
-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
-=-=-=-=-=-=-=-=-=-=-=-=-= BIOMOD.ensemble.models.out -=-=-=-=-=-=-=-=-=-=-=-=-=
sp.name : Plaice
expl.var.names : bTemp bSal Depth botCur slope fishInt maxT
models computed: Plaice_EMwmeanByROC_mergedData_mergedRun_mergedAlgo
models failed: none
-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
-=-=-=-=-=-=-=-=-=-=-=-=-=-=-= BIOMOD.models.out -=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
Modeling folder : C:/Github_projects/SDM_Claire/model output/20240917/PA
Species modeled : Cod
Modeling id : Cod_2005_2022_AllYear
Considered variables : bTemp bSal Depth botCur slope fishInt maxT
Computed Models : Cod_allData_RUN1_GLM Cod_allData_RUN1_GBM
Cod_allData_RUN1_RF Cod_allData_RUN1_XGBOOST Cod_allData_RUN2_GLM
Cod_allData_RUN2_GBM Cod_allData_RUN2_RF Cod_allData_RUN2_XGBOOST
Cod_allData_allRun_GLM Cod_allData_allRun_GBM Cod_allData_allRun_RF
Cod_allData_allRun_XGBOOST
Failed Models : Cod_allData_RUN1_GAM Cod_allData_RUN2_GAM
Cod_allData_allRun_GAM
-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
-=-=-=-=-=-=-=-=-=-=-=-=-= BIOMOD.ensemble.models.out -=-=-=-=-=-=-=-=-=-=-=-=-=
sp.name : Cod
expl.var.names : bTemp bSal Depth botCur slope fishInt maxT
models computed: Cod_EMwmeanByROC_mergedData_mergedRun_mergedAlgo
models failed: none
-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
6 Abundansmodell (SDM)
class : sdmModels
========================================================
number of species : 1
number of modelling methods : 3
names of modelling methods : glm, brt, rf
replicate.methods (data partitioning) : subsampling
number of replicates (each method) : 2
toral number of replicates per model : 2 (per species)
test percentage (in subsampling) : 25
------------------------------------------
model run success percentage (per species) :
------------------------------------------
method Plaice
----------------------
glm : 100 %
brt : 100 %
rf : 100 %
###################################################################
model Mean performance (per species), using test dataset (generated using partitioning):
-------------------------------------------------------------------------------
## species : Plaice
=========================
methods : RMSE | COR | MAE | Deviance
-------------------------------------------------------------------------
glm : 1074.15 | 0.31 | 436.61 | -865.19
brt : 1075.9 | 0.41 | 420.38 | -898.91
rf : 1014.34 | 0.45 | 430.33 | -703.06
``` modelID species method replication replicationID success training test.dep
1 1 Plaice glm subsampling 1 TRUE TRUE TRUE
2 2 Plaice glm subsampling 2 TRUE TRUE TRUE
3 3 Plaice brt subsampling 1 TRUE TRUE TRUE
4 4 Plaice brt subsampling 2 TRUE TRUE TRUE
5 5 Plaice rf subsampling 1 TRUE TRUE TRUE
6 6 Plaice rf subsampling 2 TRUE TRUE TRUE
test.indep
1 FALSE
2 FALSE
3 FALSE
4 FALSE
5 FALSE
6 FALSE
class : sdmModels
========================================================
number of species : 1
number of modelling methods : 3
names of modelling methods : glm, brt, rf
replicate.methods (data partitioning) : subsampling
number of replicates (each method) : 2
toral number of replicates per model : 2 (per species)
test percentage (in subsampling) : 25
------------------------------------------
model run success percentage (per species) :
------------------------------------------
method Cod
----------------------
glm : 100 %
brt : 100 %
rf : 100 %
###################################################################
model Mean performance (per species), using test dataset (generated using partitioning):
-------------------------------------------------------------------------------
## species : Cod
=========================
methods : RMSE | COR | MAE | Deviance
-------------------------------------------------------------------------
glm : 764.86 | 0.35 | 392.6 | -702.1
brt : 630.03 | 0.41 | 232.94 | -487.34
rf : 785.83 | 0.41 | 343.93 | -572.55
``` modelID species method replication replicationID success training test.dep
1 1 Cod glm subsampling 1 TRUE TRUE TRUE
2 2 Cod glm subsampling 2 TRUE TRUE TRUE
3 3 Cod brt subsampling 1 TRUE TRUE TRUE
4 4 Cod brt subsampling 2 TRUE TRUE TRUE
5 5 Cod rf subsampling 1 TRUE TRUE TRUE
6 6 Cod rf subsampling 2 TRUE TRUE TRUE
test.indep
1 FALSE
2 FALSE
3 FALSE
4 FALSE
5 FALSE
6 FALSE
